Relative impact of GPSRO on forecast error

Tom Auligné, Hans Huang, Hui-Chuan Lin, Xiaoyan Zhang, Xin Zhang

National Center for Atmospheric Research

NCAR is sponsored by the National Science Foundation

Goal: Community WRF DA system for • regional/global• research/operations• deterministic/probabilistic

Techniques: • 3D-Var• 4D-Var• Ensemble• Hybrid Variational/Ensemble

WRF Data Assimilation system

WRFDA Observations

In-Situ:- Surface (SYNOP, METAR, SHIP, BUOY).- Upper air (TEMP, PIBAL, AIREP, ACARS, TAMDAR).

• Remotely sensed retrievals:- Atmospheric Motion Vectors (geo/polar).- SATEM thickness.- Ground-based GPS Total Precipitable Water/Zenith Total Delay.- SSM/I oceanic surface wind speed and TPW.- Scatterometer oceanic surface winds.- Wind Profiler.- Radar radial velocities and reflectivities.- Satellite temperature/humidity/thickness profiles.- GPS refractivity (e.g. COSMIC).

Radiative Transfer (RTTOV or CRTM):– HIRS from NOAA-16, NOAA-17, NOAA-18, NOAA-19, METOP-2– AMSU-A from NOAA-15, NOAA-16, NOAA-18, NOAA-19, EOS-Aqua, METOP-2– AMSU-B from NOAA-15, NOAA-16, NOAA-17– MHS from NOAA-18, NOAA-19, METOP-2– AIRS from EOS-Aqua– SSMIS from DMSP-16

•Bogus: – TC bogus.– Global bogus.

From Langland and Baker (2004)

ForecastError

xt is the true state, estimated by the analysis at the time of the forecastxf is the forecast from analysis xaxg is the forecast from first-guess at the time of the analysis xa

e is the verification norm (e.g. Total Dry Energy)

Time

Impact of Observations on Forecast Error

Observation(y)

WRFData

Assimilation

WRF-ARWModel

Forecast(xf)

DeriveForecastAccuracy

Background(xb)

Analysis(xa)

Adjoint of WRF-ARW

Linear Model

ObservationSensitivity(δF/ δy)

Observation Impact

<y-H(xb)> (δF/ δy)

Adjoint of WRF Data

Assimilation

DefineForecastAccuracy

ForecastAccuracy

(F)

Figure adapted from Liang Xu (NRL)

UpdateBC

Adjoint ofUpdate

BC

Impact of Observations on Forecast Error

12h Forecast error reduction against ERA

Observation impact for Arctic System Reanalysis

Observation impact for Arctic System Reanalysis

Observation impact for CONUS

June January

Observation impact for Taiwan CWB operations

Observation impact for Taiwan CWB operations

Summary

• GPSRO observations consistently reduce WRF forecast error • various domains, periods, experimental setups• different platforms• 00, 06, 12 and 18UTC

• GPSRO has a large impact per observation.(comparable results at AFWA and Met Office)

• Linear assumption (Adjoint of the forecast model and analysis)

• Approximation of the “truth” for calculation of forecast error

• Results depend on the choice of norm

• Does not include accumulated and indirect impact

Limitations